Land use change drives the spatio-temporal variation of ecosystem services and their interactions along an altitudinal gradient in Brazil

Gomes, Lucas Carvalho; Bianchi, Felix J.J.A.; Cardoso, Irene Maria; Filho, Elpı́dio Inácio Fernandes; Schulte, Rogier P.O.

doi:10.1007/s10980-020-01037-1

Cited by 59 publications

(28 citation statements)

References 64 publications

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“…Biophysical conditions, including temperature, precipitation, evapotranspiration, soil type, and ultimately vegetation type, can vary dramatically in mountain systems [16]. Therefore, the spatial heterogeneity of ESs is high [17]. However, we still have a limited understanding of how to construct landscape units to reflect spatial heterogeneity and how provisioning patterns of multiple ESs emerge and change in space and time along the landscape and terrain gradients in mountain systems.…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Variation in Ecosystem Services and Their Drivers among Different Landscape Heterogeneity Units and Terrain Gradients in the Southern Hill and Mountain Belt, China

Wang

Jiang

et al. 2021

Remote Sensing

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Understanding the spatiotemporal heterogeneity of ecosystem services (ESs) and their drivers in mountainous areas is important for sustainable ecosystem management. However, the effective construction of landscape heterogeneous units (LHUs) to reflect the spatial characteristics of ESs remains to be studied. The southern hill and mountain belt (SHMB) is a typical mountainous region in China, with undulating terrain and obvious spatial heterogeneity of ESs, and was selected as the study area. In this study, we used the fuzzy k-means (FKM) algorithm to establish LHUs. Three major ESs (water yield, net primary productivity (NPP), and soil conservation) in 2000 and 2015 were quantified using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model and Carnegie Ames-Stanford approach (CASA) model. Then, we explored the spatial variation in ESs along terrain gradients and LHUs. Correlation analysis was used to analyze the driving factors of ESs in each terrain region and LHU. The results showed that altitude and terrain niche increased along LHUs. Water yield and soil conservation increased from 696.86 mm and 3920.19 t/km2 to 1061.12 mm and 5117.90 t/km2, respectively, while NPP decreased from 666.95 gC/m2 to 648.86 gC/m2. The ESs in different LHUs differed greatly. ESs increased first and then decreased along LHUs in 2000. In 2015, water yield decreased along LHUs, while NPP and soil conservation showed a fluctuating trend. Water yield was mainly affected by precipitation, temperature and NDVI were the main drivers of NPP, and soil conservation was greatly affected by precipitation and slope. The driving factors of the same ES were different in different terrain areas and LHUs. The variation and driving factors of ESs in LHUs were similar to some terrain gradients. To some extent, LHUs can represent multiple terrain features. This study can provide important support for mountain ecosystem zoning management and decision-making.

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Section: Introductionmentioning

confidence: 99%

Spatiotemporal Variation in Ecosystem Services and Their Drivers among Different Landscape Heterogeneity Units and Terrain Gradients in the Southern Hill and Mountain Belt, China

Wang

Jiang

et al. 2021

Remote Sensing

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“…High demands for food, timber, energy, housing, and other goods and services to meet the demands of more than 7 billion people worldwide—as well as the shifts in land management efforts to enhance some ES but at the cost of reductions in many ES—have resulted in the degradation of global ecosystem services at unprecedented intensities and rates [ 3 ]. Among all human activities, land-use and land-cover change (LUCC) is always the significant factor affecting the composition and configuration of ecosystems that leads to a change in the provision of ecosystem services [ 2 , 4 , 5 ], as some ES are closely related to specific land-use types [ 6 ]. For example, the conversion of grasslands, forests, and water areas into croplands and developed areas has led to a substantial increase in the production of food, housing, and other commodities [ 7 ].…”

Section: Introductionmentioning

confidence: 99%

“…In our study, to effectively evaluate the impacts of land-use change on ES, we linked the GeoSOS-FLUS (Sun Yat-sen University, Guangzhou, China) and InVEST (Integrated Valuation of Ecosystem Service and Tradeoffs) models (Stanford University, Palo Alto, CA, USA), which are both suitable for application under different scenarios [ 6 , 8 , 30 ]. The GeoSOS-FLUS model was used to quantify the changes in land-use between the years 2000, 2015, and 2030, under three scenarios: (1) Business As Usual (BAU), (2) Rapid Urban Development (RUD), and (3) Ecological Protection (ELP).…”

Section: Introductionmentioning

confidence: 99%

Analyzing Land-Use Change Scenarios for Ecosystem Services and their Trade-Offs in the Ecological Conservation Area in Beijing, China

Cheng

Han

2020

IJERPH

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It is generally believed that land-use changes can affect a variety of ecosystem services (ES), but the relationships involved remain unclear due to a lack of systematic knowledge and gaps in data. In order to make rational decisions for land-use planning that is grounded in a systematic understanding of trade-offs between different land-use strategies, it is very important to understand the response mechanisms of various ecosystem services to changes in land-use. Therefore, the objective of our study is to assess the effects of land-use change on six ecosystem services and their trade-offs among the ecosystem services in the ecological conservation area (ECA) in Beijing, China. To do this, we projected future land-use in 2030 under three different scenarios: Business as Usual (BAU), Ecological Protection (ELP), and Rapid Urban Development (RUD), using GeoSOS-FLUS model. Then, we quantified six ecosystem services (carbon storage, soil conservation, water purification, habitat quality, flood regulation, and food production) in response to land-use changes from 2015 to 2030, using a spatially explicit InVEST model. Finally, we illustrated the trade-offs and/or synergistic relationships between each ecosystem service quantified under each of the different scenarios in 2030. Results showed that built-up land is projected to increase by 281.18 km2 at the cost of water bodies and cultivated land from 2015 to 2030 under the RUD scenario, while forest land is projected to increase by 152.38 km2 under the ELP scenario. The carbon storage, soil conservation, habitat quality, and the sum of ecosystem services (SES) would enrich the highest level under the ELP scenario. Land-use strategies that follow the ELP scenario can better maintain the ecosystem services and sustainable development of natural and social economic systems.

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“…A better understanding of land dynamics requires the detection of LULC changes [22]. Empirical studies by researchers from various disciplines have shown that changes in LULC are key to various applications, such as hydrology, agriculture, forestry, the environment, geology, and ecology [1,2,23,24]. Many researchers argue that LULC change could result in an ecosystem imbalance and impacts on the environment caused by humans and their role in climate change [25][26][27][28].…”

Section: Introductionmentioning

confidence: 99%

Land Use and Land Cover Changes in the Diversity and Life Zone for Uncontacted Indigenous People: Deforestation Hotspots in the Yasuní Biosphere Reserve, Ecuadorian Amazon

Heredia-R

Torres

Cabrera-Torres

et al. 2021

Forests

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Land use and land cover change (LULC) is an essential component for the monitoring environmental change and managing natural resources in areas of high natural and cultural biodiversity, such as the Amazon biome. This study was conducted in in the northern Amazon of Ecuador, specifically in the Diversity and Life Zone (DLZ) of the Yasuní Biosphere Reserve (YBR). The general aim was to investigate the territorial dynamics of land use/land cover changes to support policies for environmental and sociocultural protection in the DLZ. Specific objectives included (i) mapping LULC spatial and temporal dynamics in the DLZ in the period from 1999 to 2018, (ii) identifying sensitive LULC hotspots within the DLZ, and (iii) defining the possible policy implications for sustainable land use in the DLZ. Multitemporal satellite imagery from the Landsat series was used to map changes in LULC, which were divided into three-time stages (1999–2009, 2009–2018, 1999–2018). We adopted open-access Landsat images downloaded from the United States Geological Survey (USGS). The processes for assessing LULC in the DLZ included (1) data collection and analysis, (2) data processing for remote sensing, (3) thematic land cover, and (4) homogenization and vectorization of images. The results showed that in the period 1999–2018, most of the uses and land cover were transformed into pastures in the DLZ. Therefore, it is important to improve territorial planning, to avoid conflicts between indigenous populations, migrant settlers, and uncontacted indigenous populations that live in the DLZ, within the YBR.

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Land use change drives the spatio-temporal variation of ecosystem services and their interactions along an altitudinal gradient in Brazil

Cited by 59 publications

References 64 publications

Spatiotemporal Variation in Ecosystem Services and Their Drivers among Different Landscape Heterogeneity Units and Terrain Gradients in the Southern Hill and Mountain Belt, China

Spatiotemporal Variation in Ecosystem Services and Their Drivers among Different Landscape Heterogeneity Units and Terrain Gradients in the Southern Hill and Mountain Belt, China

Analyzing Land-Use Change Scenarios for Ecosystem Services and their Trade-Offs in the Ecological Conservation Area in Beijing, China

Land Use and Land Cover Changes in the Diversity and Life Zone for Uncontacted Indigenous People: Deforestation Hotspots in the Yasuní Biosphere Reserve, Ecuadorian Amazon

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